A semi-parametric empirical likelihood approach for conditional estimating equations under endogenous selection

The estimation and inference for conditional estimating equations models with endoge-nous selection, are considered. The approach takes into account possible endogenous selec-tion which may lead to a selection bias. It can be used for a wide range of statistical mod-els not covered by the model-based sampling theory. Endogeneity can be either part of the selection or within the covariates. It is particularly well suited for models with unknown heteroscedasticity, uncontrolled confounders and measurement errors. It will not be nec-essary to model the relationship between the endogenous covariates and the instrumental variables, which offers major advantages over two-stage least-squares. The approach pro-posed has the advantage of being based on a fixed number of constraints determined by the size of the parameter.(c) 2021 EcoSta Econometrics and Statistics. Published by Elsevier B.V. All rights reserved.